Many research works on soft,sensors have been conducted. Although it is common practice to evaluate the estimation performance of soft-sensors by using industrial process data, few papers have reported long-term application results of process control using soft-sensors in real processes In the present Work, a practical configuration of an inferential Control system was developed that integrated a commercial model predictive control (MPC) software and a just-in:time (PT) soft-sensor. The developed system has adopted locally weighted partial least squares (LW-PLS) to built! soft sensors LW-PLS is a kind of JIT Modeling method that can cope with. changes in process characteristics as well as process nonlinearity. Thus,. LW-PLS helps engineers to reduce their burden of model maintenance, which has been organized as the most serious problem in practice. The usefulness of the developed LW-PLS-based soft-sensors and inferential control systems is demonstrated through their successful industrial applications to a cracked gasoline (CGL) fractionator and a purification section for an acetyl plant Inferential control Systems have been used for more than a year at Showa Denko K.K. (SDK) in Japan. The Operation cost and environmental burden have been significantly reduced. In the CGL fractionator, for example, about 0.6% of operation cost was cut successfully. In addition, the present work aims to describe challenges, revealed by the long-term applications of JIT soft-sensors: the parameter tuning, the selection of input variables, the definition of similarity in JIT modeling, the management of the database, and the assessment and enhancement of soft-sensor reliability.